Acupuncture is a well-known form of complementary medicine that is increasingly being used worldwide. Despite being rare, pneumothorax is the most common serious complication described in acupuncture. A 79-year-old woman was admitted to the emergency department with a pneumothorax. Two days before, she had undergone an acupuncture treatment for chronic back pain. She felt a sharp right shoulder pain as needles were inserted in the interscapular area. As the pain did not resolve, she consulted her general practitioner and had a chest radiography done, revealing a right-sided pneumothorax. At the hospital, a right chest tube was inserted with relief of the symptoms and lung expansion. The chest tube was removed on the second day of admission, and she was discharged on the third day. Both acupuncturists and clinicians need to be aware of the possibility of adverse events following acupuncture, especially in those who develop symptoms.

Sclerosing mesenteritis is a rare benign disease presenting with chronic inflammation of the mesenteric adipose tissue and variable degrees of fibrosis. A 47-year-old black man presented to the emergency department with symptoms of small bowel obstruction, requiring surgical treatment. The laparotomy revealed a stenosis of the distal ileum with mesenteric thickening and an enterectomy was performed. The postoperative period was complicated by the maintenance of bowel obstruction. The patient underwent a second laparotomy, in which the fibrosing process of the mesentery was much aggravated, and an ileo-colic resection was needed. After knowledge of the histological diagnosis, the patient was started on immunomodulators with clinical improvement. At 26 months of follow-up, patient is asymptomatic under medical treatment. This is the first report, to our knowledge, of a patient with progressive fibrosis in such short period of time requiring surgical re-intervention for bowel obstruction, owing to sclerosing mesenteritis.

Pancreatic ductal adenocarcinoma is an invasive tumor with similar incidence and mortality rates. Pancreaticoduodenectomy has morbidity and mortality rates of up to 60% and 5%, respectively. The purpose of our study was to assess preoperative features contributing to unfavorable 1-year survival prognosis. Study Design: Retrospective, single-center study evaluating the impact of preoperative features on short-term survival outcomes in head PDAC patients. Forty-four prior features of 172 patients were tested using different supervised machine learning models. Patient records were randomly divided into training and validation sets (80–20%, respectively), and model performance was assessed by area under curve (AUC) and classification accuracy (CA). Additionally, 33 patients were included as an independent revalidation or holdout dataset group. Results: Eleven relevant features were identified: age, sex, Ca-19-9, jaundice, ERCP with biliary stent, neutrophils, lymphocytes, lymphocyte/neutrophil ratio, neoadjuvant treatment, imaging tumor size, and ASA. Tree regression (tree model) and logistic regression (LR) performed better than the other tested models. The tree model had an AUC = 0.92 and CA = 0.85. LR had an AUC = 0.74 and CA = 0.78, allowing the development of a nomogram based on absolute feature significance. The best performance model was the tree model which allows us to have a decision tree to help clinical decisions. Discussion and conclusions: Based only on preoperative data, it was possible to predict 1-year survival (91.5% vs. 78.1% alive and 70.9% vs. 76.6% deceased for the tree model and LR, respectively). These results contribute to informed decision-making in the selection of which patients with PDAC can benefit from pancreatoduodenectomy. A machine learning algorithm was developed for the recognition of unfavorable 1-year survival prognosis in patients with pancreatic ductal adenocarcinoma. This will contribute to the identification of patients who would benefit from pancreatoduodenectomy. In our cohort, the tree regression model had an AUC = 0.92 and CA = 0.85, whereas the logistic regression had an AUC = 0.74 and CA = 0.78. To further inform decision-making, a decision tree based on tree regression was developed.

A 54-year-old man was admitted to the emergency department for upper intestinal bleeding which was diagnosed during an upper endoscopy. Seventeen months before, the patient had a laparoscopic gastric band procedure, with a body mass index of 51 kg/m2 and had lost 50 kg since then. He only

Background: Simultaneous pancreas–kidney (SPK) transplantation can restore renal function and insulin independence, but non-technical pancreas graft dysfunction remains difficult to anticipate. Methods: We conducted an exploratory single-centre retrospective biomarker-modelling study to determine whether day-zero recipient serum Fourier-transform infrared (FTIR) spectra are associated with subsequent loss of insulin independence after SPK transplantation. Results: Among 104 screened recipients, 51 met predefined sample-availability, spectral-quality, data-linkage and endpoint-adjudication criteria; 30 maintained pancreas graft function and 21 developed dysfunction. Cases dominated by early technical surgical failure were excluded. Clinical-only, FTIR-only and FTIR–clinical Naïve Bayes models were evaluated using leave-one-out cross-validation with Fast Correlation-Based Filter feature selection. In locked-feature internal validation, the best FTIR-only model used second-derivative spectra with vector normalization and nine selected wavenumbers, achieving AUC 0.997 (95% CI 0.985–1.000) and accuracy 0.961 (95% CI 0.902–1.000). A fixed-feature permutation analysis exceeded label-randomized performance (empirical p = 0.001). The secondary Group 1 versus Group 3 analysis suggested discrimination of pancreas dysfunction despite preserved kidney function (AUC 0.992; accuracy 0.930). Conclusions: Given the small cohort, high-dimensional input, non-nested feature selection, selection-bias risk and absence of external validation, serum FTIR should be considered a candidate risk-enrichment platform requiring prospective multicentre validation.